Latest revision as of 09:39, 13 November 2012

Contents

The Parallel GHC Project is an MSR-funded project to push the real-world use of parallel Haskell. The aim is to demonstrate that parallel Haskell can be employed successfully in industrial projects.

In the last few years GHC has gained impressive support for parallel programming on commodity multi-core systems. In addition to traditional threads and shared variables, it supports pure parallelism, software transactional memory (STM), and data parallelism. With much of this research and development complete, the next stage is to get the technology into more widespread use.

This project aims to do the engineering work to solve whatever remaining practical problems are blocking organisations from making serious use of parallelism with GHC. The driving force is the applications rather than the technology.

The project involves a partnership with six groups from commercial and scientific organisations. Over the course of two years these groups are applying parallel Haskell in their specific domains. They are being supported by GHC HQ and Well-Typed who are providing advice on Haskell tools and techniques, and applying engineering effort to resolve any issues that are hindering these groups' progress.

The project is being coordinated by Well-Typed and they are providing the bulk of the support and engineering effort. The project started in the summer of 2010.

We have been continuing our work to make ThreadScope more helpful and informative in tracking down your parallel and concurrent Haskell performance problems. We now have the ability to collect heap (and some other) statistics from the GHC runtime system and present them in ThreadScope for a selected runtime interval. These features are available for users of GHC 7.6 or newer. On feedback from users, we have improved support for user events of different granularity. We have released a preliminary version of tools for collecting information from hardware performance counters, more specifically the Linux Perf Events. This can be useful for studying IO-heavy programs, the idea being to visualise system calls as being distinct from actual execution of Haskell code. The perf events support will be available for users of a recent development GHC (7.7.x) or the eventual 7.8 release.

The reimplementation of Cloud Haskell is now avaiable from Hackage and in a state where it is ready for serious experiments. Compared to the prototype it is much faster; it can run on multiple kinds of networks;
it has backends to support different environments (like cluster or cloud, with a proof-of-concept backend for Azure);
has a new system for dealing with node disconnect and reconnect, and a more precisely defined semantics; supports composable, polymorphic serialisable closures; and internally the code is better structured and easier to work with.

The wiki lists some important open issues of the implementation; the semantics document mentioned above lists some important open semantic issues.

We have been publishing a regular newsletter containing project news, other parallel news from around the Haskell community and short "Word of the Month" articles giving brief introductions to important concepts in parallelism.

The Cloudy Bayes project aims to develop a fast Bayesian model fitter that takes advantage of modern multiprocessor machines. It will support model descriptions in the BUGS model description language (WinBUGS, OpenBUGS, and JAGS). It will be implemented as an embedded domain specific language (EDSL) within Haskell. A wide range of model hierarchical Bayesian model structures will be possible, including many of the models used in medical, ecological, and biological sciences.

Cloudy Bayes will provide an easy to use interface for describing models, running Monte Carlo Markov chain (MCMC) fitters, diagnosing performance and convergence criteria as it runs, and collecting output for post-processing. Haskell's strong type system will be used to ensure that model descriptions make sense, providing a fast, safe development cycle.

Haskell is suitable for many kinds of domain, and GHC's support for lightweight threads makes it attractive for concurrency applications. An exception has been network server programming because GHC 6.12 and earlier have an IO manager that is limited to 1024 network sockets. GHC 7 has a new IO manager implementation that gets rid of this limitation.

This project will implement several network servers to demonstrate that Haskell is suitable for network servers that handle a massive number of concurrent connections.

This project will use parallel Haskell to implement high-performance Monte Carlo algorithms, a class of algorithms which use randomness to sample large or otherwise intractable solution spaces. The initial goal is a particle-based MC algorithm suitable for modeling the flow of radiation, with application to problems in astrophysics. From this, the project is expected to move to identification of suitable abstractions for expressing a wider variety of Monte Carlo algorithms, and using models for different physical phenomena.

This project will drive API, performance, and profiling tool requirements for Haskell's interface to the Message Passing Interface (MPI) specification, an industry-standard in High Performance Computing (HPC), as used on clusters of many nodes.

Competing internal initiatives use C++/MPI and CUDA directly.

Willow Garage aims to lay the groundwork for personal robotics applications in everyday life. ROS (Robot Operating System) is an open source, meta-operating system for your robot.

This project is to demonstrate parallel Haskell technology using the example of graph algorithms in large graphs representing social networks. The current work is on parallel versions of the Bron-Kerbosch algorithm for finding maximal cliques in a graph. The initial goal is to demonstrate good speedups on multi-core and the overall aim to demonstrate good speedups of a distributed version of the algorithm using Cloud Haskell.